Abstract
Abstract. This paper addresses the question of how much uncertainties in CO2 fluxes over Australia can be reduced by assimilation of total-column carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite instrument. We apply a four-dimensional variational data assimilation system, based around the Community Multiscale Air Quality (CMAQ) transport-dispersion model. We ran a series of observing system simulation experiments to estimate posterior error statistics of optimized monthly-mean CO2 fluxes in Australia. Our assimilations were run with a horizontal grid resolution of 81 km using OCO-2 data for 2015. Based on four representative months, we find that the integrated flux uncertainty for Australia is reduced from 0.52 to 0.13 Pg C yr−1. Uncertainty reductions of up to 90 % were found at grid-point resolution over productive ecosystems. Our sensitivity experiments show that the choice of the correlation structure in the prior error covariance plays a large role in distributing information from the observations. We also found that biases in the observations would significantly impact the inverted fluxes and could contaminate the final results of the inversion. Biases in prior fluxes are generally removed by the inversion system. Biases in the boundary conditions have a significant impact on retrieved fluxes, but this can be mitigated by including boundary conditions in our retrieved parameters. In general, results from our idealized experiments suggest that flux inversions at this unusually fine scale will yield useful information on the carbon cycle at continental and finer scales.
Highlights
The future of climate change depends mainly on the trajectory of greenhouse gas concentrations in the Earth’s atmosphere, in particular carbon dioxide (CO2) (Arora et al, 2013)
This paper aims to assess the likely uncertainty reduction for CO2 fluxes over Australia using a series of observing system simulation experiments (OSSEs) and to test our fourdimensional flux-inversion scheme
The main findings indicate that Orbiting Carbon Observatory-2 (OCO-2) nadir and glint data can provide a moderate (≈ 30 %) to significant (> 70 %) constraint on the Australian CO2 flux uncertainty in 2015
Summary
The future of climate change depends mainly on the trajectory of greenhouse gas concentrations in the Earth’s atmosphere, in particular carbon dioxide (CO2) (Arora et al, 2013). Quantifying the terrestrial–atmosphere and ocean– atmosphere carbon exchanges is relevant for understanding the carbon cycle and climate since they play an important role by absorbing more than half of anthropogenic CO2 emissions (Ciais et al, 2013). Future predictions from most of the dynamic global vegetation models (DGVMs) are highly uncertain about the behaviour of the carbon cycle (Sitch et al, 2008). Reducing the regional-scale CO2 flux uncertainties in these biogeochemical models (Canadell et al, 2010, 2011) is crucial to ascertain more accurate estimates of future climate projections (Friedlingstein et al, 2006; Huntingford et al, 2009; Friedlingstein et al, 2014). Inverse modelling of CO2 fluxes (Ciais et al, 2010; Rayner et al, 2019) can potentially help to constrain these uncertainties (Chevallier et al, 2010b) by directly using information from atmospheric CO2 concentrations (Chevallier et al, 2005a, 2007; Baker et al, 2010)
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